{"id":"W4412260724","doi":"","title":"What’s in the Box? The Legal Requirement to Explain Computationally Aided Decision-Making in Public Administration","year":2021,"lang":"en","type":"article","venue":"Research at the University of Copenhagen (University of Copenhagen)","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for International Governance Innovation","funders":"Copenhagen Graduate School for Nanoscience and Nanotechnology; Danmarks Grundforskningsfond; National Research Foundation; Innovationsfonden","keywords":"Administration (probate law); Computer science; Political science; Business; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.007268889,0.000116632,0.0002270829,0.000238396,0.002264988,0.0002489898,0.002376026,0.0001082006,0.03455506],"category_scores_gemma":[0.001232382,0.0001062683,0.000108633,0.002077003,0.0006974324,0.001805734,0.001280987,0.0004167808,0.002729193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006136039,"about_ca_system_score_gemma":0.001487938,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003278957,"about_ca_topic_score_gemma":0.1554366,"domain_scores_codex":[0.9942927,0.003068044,0.0002192317,0.0003846139,0.001571007,0.0004643852],"domain_scores_gemma":[0.9966969,0.001777182,0.0001591397,0.0006371928,0.0006097685,0.0001197975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001204184,0.0004672527,0.00004336111,0.00004754715,0.00007377787,0.0005334544,0.08699844,0.0003150997,0.0007375986,0.01817263,0.8728839,0.01852277],"study_design_scores_gemma":[0.0007739615,0.0001547232,0.01446952,0.000174109,0.00001664573,0.000006021939,0.2679908,0.0002920816,0.0001967279,0.0006336287,0.7151476,0.0001441304],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7951735,0.002369213,0.01191663,0.09106386,0.0003019606,0.002826851,0.00006953786,0.00003244579,0.096246],"genre_scores_gemma":[0.979683,0.0004088999,0.0007656246,0.0001589243,0.00003029902,6.897409e-7,0.00003232166,0.000005922609,0.01891434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1845095,"threshold_uncertainty_score":0.9990339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08859363201453696,"score_gpt":0.3609546116106667,"score_spread":0.2723609795961297,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}